ZoomInfo has been busy over the last few months. The company first debuted its AI Copilot tool set on May 21st. The company quickly followed up with a pre-packaged integration with Gong this week.
The Copilot is what you would expect: taking the most relevant buying signals — intent spikes, key hires and personnel moves, insights from our partner ecosystem, and the B2B company and contact data ZoomInfo has been known for - and pushing that insight to sellers. These alerts can be shared across multiple channels, allowing teams to quickly triage emerging opportunities and act decisively on high-quality intent signals.
The Copilot can be used by marketing teams as well. According to ZoomInfo marketers can access a ranked and prioritized list of the companies and buyers in-market, based on the high volume of signals analyzed and prioritized by ZoomInfo Copilot’s AI every day. The gen AI capabilities allow for typical Gen AI use cases for sellers: account and opportunity summaries, suggested accounts to engage that might be overlooked, etc.
The new Copilot integrates with Salesforce and Hubspot, and can link to other CRM systems as well - but the integration with Gong is eyebrow raising on a few levels. The combination of call records and other interaction data meshed with ZoomInfo’s large data set - attacked by AI - can offer up even more timely recommendations, prioritized outreach plans, uncover buying committee members that might be present on calls but NOT in the CRM, etc.
As go-to-market teams look to be more data-centric, and leverage AI, the good news is that a lot of revenue platform tools are coalescing to create a type of Customer Data Value chain, breaking down the silos (so you don’t have to!) to get at a richer, wider set of customer data in order to show value through AI.
We are getting to a tipping point, where AI is both so embedded in common go-to-market tools, and the need to stay competitive are both so high that nearly all B2B firms must be at least dipping their toes in the water in terms of AI and creating far more expansive customer views. Again, the good news is the “heavy lifting” to get to a Customer Data Value Chain model is becoming less and less arduous.
Of course, with all AI tools, building out an internal usage policy and governance team is essential. But the implementation side of things is becoming less of a burden, with more impetus to act rather than sit on the wayside in strategy, rather than action mode.
